Demand response refers to mechanisms used to encourage/induce utility consumers to curtail or shift their demand at particular times in order to reduce aggregate utility demand. For example, electric utilities employ demand response solutions to reduce peak demand for electricity. Demand response programs typically offer customers incentives for agreeing to reduce their demand at certain times. Many of these programs stipulate that the utilities can invoke a limited number of demand response/curtailment (e.g., critical peak pricing) events in a given time period (e.g., 20 per year). Therefore, utilities would like to invoke curtailment events only on those occasions when utility demand and generation costs are among the highest. However, for various reasons including weather, utility demand cannot be forecasted with certainty, especially for long time periods into the future. While short-term (e.g. within 24 hours) demand may be known within reasonable bounds, longer-term demand (e.g., weeks or longer) can at best be estimated as a probability distribution.
To date, utilities typically use simple heuristic based triggers, such as temperature or reserve margin, to determine when to invoke a demand response or curtailment event. However, this approach does not provide the utilities with the best opportunity to exercise the option of economic load shedding or curtailment so that their gains, savings, and/or other criteria are optimized.
For these and other reasons, there is a need for the present invention.